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Event‐specific data envelopment models and efficiency analysis

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  • Robert G. Chambers
  • Atakelty Hailu
  • John Quiggin

Abstract

Most, if not all, production technologies are stochastic. This article demonstrates how data envelopment analysis (DEA) methods can be adapted to accommodate stochastic elements in a state-contingent setting. Specifically, we show how observations on a random input, not under the control of the producer and not known at the time that variable input decisions are made, can be used to partition the state space in a fashion that permits DEA models to approximate an event-specific production technology. The approach proposed in this article uses observed data on random inputs and is easy to implement. After developing the event-specific DEA representation, we apply it to a data set for Western Australian wheat farmers. Our results highlight the need for acknowledging stochastic elements in efficiency analysis.
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Suggested Citation

  • Robert G. Chambers & Atakelty Hailu & John Quiggin, 2011. "Event‐specific data envelopment models and efficiency analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 55(1), pages 90-106, January.
  • Handle: RePEc:bla:ajarec:v:55:y:2011:i:1:p:90-106
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    References listed on IDEAS

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    1. Léopold Simar & Paul Wilson, 2000. "Statistical Inference in Nonparametric Frontier Models: The State of the Art," Journal of Productivity Analysis, Springer, vol. 13(1), pages 49-78, January.
    2. John Quiggin & David Adamson & Sarah Chambers & Peggy Schrobback, 2010. "Climate Change, Uncertainty, and Adaptation: The Case of Irrigated Agriculture in the Murray-Darling Basin in Australia," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 58(s1), pages 531-554, December.
    3. Chambers,Robert G. & Quiggin,John, 2000. "Uncertainty, Production, Choice, and Agency," Cambridge Books, Cambridge University Press, number 9780521622448, October.
    4. Banker, Rajiv D. & Chang, Hsihui, 1995. "A simulation study of hypothesis tests for differences in efficiencies," International Journal of Production Economics, Elsevier, vol. 39(1-2), pages 37-54, April.
    5. Fraser, Iain & Graham, Mary, 2005. "Efficiency Measurement of Australian Dairy Farms: National and Regional Performance," Australasian Agribusiness Review, University of Melbourne, Melbourne School of Land and Environment, vol. 0.
    6. Robert G. Chambers & Erik Lichtenberg, 1996. "A Nonparametric Approach to the von Liebig-Paris Technology," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 78(2), pages 373-386.
    7. Chambers, Christopher P. & Miller, Alan D., "undated". "Inefficiency," Working Papers WP2011/14, University of Haifa, Department of Economics, revised 30 Nov 2011.
    8. Rajiv D. Banker, 1993. "Maximum Likelihood, Consistency and Data Envelopment Analysis: A Statistical Foundation," Management Science, INFORMS, vol. 39(10), pages 1265-1273, October.
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    Cited by:

    1. Theodoros Skevas & Teresa Serra, 2016. "The role of pest pressure in technical and environmental inefficiency analysis of Dutch arable farms: an event-specific data envelopment approach," Journal of Productivity Analysis, Springer, vol. 46(2), pages 139-153, December.
    2. repec:kap:jproda:v:48:y:2017:i:1:d:10.1007_s11123-017-0507-5 is not listed on IDEAS
    3. Skevas, Theodoros & Lansink, Alfons Oude & Stefanou, Spiro E., 2012. "Measuring technical efficiency in the presence of pesticide spillovers and production uncertainty: The case of Dutch arable farms," European Journal of Operational Research, Elsevier, vol. 223(2), pages 550-559.
    4. Serra, Teresa & Oude Lansink, Alfons, 2014. "Measuring the impacts of production risk on technical efficiency: A state-contingent conditional order-m approach," European Journal of Operational Research, Elsevier, vol. 239(1), pages 237-242.
    5. Boussemart, Jean-Philippe & Crainich, David & Leleu, Hervé, 2015. "A decomposition of profit loss under output price uncertainty," European Journal of Operational Research, Elsevier, vol. 243(3), pages 1016-1027.
    6. Kapelko, Magdalena & Oude Lansink, Alfons & Stefanou, Spiro E., 2014. "Assessing dynamic inefficiency of the Spanish construction sector pre- and post-financial crisis," European Journal of Operational Research, Elsevier, vol. 237(1), pages 349-357.
    7. Skevas, Theodoros & Stefanou, Spiro E. & Oude Lansink, Alfons, 2014. "Pesticide use, environmental spillovers and efficiency: A DEA risk-adjusted efficiency approach applied to Dutch arable farming," European Journal of Operational Research, Elsevier, vol. 237(2), pages 658-664.

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